Context rules for a graph

ABSTRACT

Examples of the present disclosure describe systems and methods relating to context rules in a graph or isolated collection. In an example, information in an isolated collection may be associated with one or more contexts. The information may be represented within the isolated collection based on one or more rules, and one or more of the rules may be associated with one or more contexts to which the information relates, thereby indicating a context association. A context association may indicate a positive, negative, or other relationship between one or more rules and one or more contexts. Based on the context association, information within the isolated collection may be adapted to generate different views of the isolated collection for different contexts. As such, relevant, useful, or actionable information may be included or emphasized, while information that is not as relevant, useful, or actionable may be omitted or deemphasized.

BACKGROUND

A graph or isolated collection may store information relating to avariety of domains, contexts, data types, users, tenants, divisions,teams, or other categories. While it may ultimately be useful to have arich body of knowledge, such a diverse set of information may complicateaccessing or identifying relevant information within the isolatedcollection.

It is with respect to these and other general considerations that theaspects disclosed herein have been made. Also, although relativelyspecific problems may be discussed, it should be understood that theexamples should not be limited to solving the specific problemsidentified in the background or elsewhere in this disclosure.

SUMMARY

Examples of the present disclosure describe systems and methods relatingto context rules in a graph or isolated collection. In an example,information in an isolated collection may be associated with one or morecontexts. The information may be represented within the isolatedcollection using one or more rules. A context association may begenerated for one or more of the rules by associating each of the ruleswith one or more contexts to which the information relates. As a result,information within the isolated collection may be adapted based on thecontext association to provide a view of the isolated collection that isrelevant to the context.

When it is determined that a rule is relevant to a given context basedon a context association, the rule may be selected or emphasized withinthe adaptation of the isolated collection. In some examples, a contextassociation may specify a negative association, such that a rule may beomitted or deemphasized within the adaptation of the isolatedcollection. By adapting the isolated collection using one or morecontext associations, it may be possible to generate different views ofan isolated collection for different contexts, such that relevant,useful, or actionable information is included or emphasized, whileinformation that is not as relevant, useful, or actionable may beomitted or deemphasized.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter. Additionalaspects, features, and/or advantages of examples will be set forth inpart in the description which follows and, in part, will be apparentfrom the description, or may be learned by practice of the disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive examples are described with reference tothe following figures.

FIG. 1 illustrates an overview of an example system for generating,applying, and/or managing a context rule for an isolated collection.

FIG. 2 illustrates an overview of an example system for managingisolated collections of resource identifiers and correspondingrelationships.

FIG. 3A illustrates an overview of an example isolated collection.

FIGS. 3B-3E illustrate an example query model that may be used totraverse an isolated collection.

FIGS. 4A-4E illustrate overviews of an example isolated collection.

FIG. 5 illustrates an overview of an example method for adapting anisolated collection based on context information.

FIG. 6 illustrates an overview of an example method for generating acontext association for an isolated collection.

FIG. 7 is a block diagram illustrating example physical components of acomputing device with which aspects of the disclosure may be practiced.

FIGS. 8A and 8B are simplified block diagrams of a mobile computingdevice with which aspects of the present disclosure may be practiced.

FIG. 9 is a simplified block diagram of a distributed computing systemin which aspects of the present disclosure may be practiced.

FIG. 10 illustrates a tablet computing device for executing one or moreaspects of the present disclosure.

DETAILED DESCRIPTION

Various aspects of the disclosure are described more fully below withreference to the accompanying drawings, which form a part hereof, andwhich show specific exemplary aspects. However, different aspects of thedisclosure may be implemented in many different forms and should not beconstrued as limited to the aspects set forth herein; rather, theseaspects are provided so that this disclosure will be thorough andcomplete, and will fully convey the scope of the aspects to thoseskilled in the art. Aspects may be practiced as methods, systems ordevices. Accordingly, aspects may take the form of a hardwareimplementation, an entirely software implementation or an implementationcombining software and hardware aspects. The following detaileddescription is, therefore, not to be taken in a limiting sense.

A graph or isolated collection may store resources and relationshipsrelating to a wide array of information (e.g., from a variety ofinformation sources, relating to different domains, etc.). Given thepotential diversity of information contained within the isolatedcollection, many different types of relationships may exist betweenresources of the isolated collection, thereby creating a rich body ofknowledge from which information may by queried or accessed. While itmay be useful to have an isolated collection containing a large breadthand/or depth of information, some amount or even a large percentage ofthe information in the isolated collection may not be applicable orrelevant at any given time. As such, identifying which parts of theinformation (e.g., rules, resources, relationships, properties, and/orattributes) are relevant to or useful for a user or client may bedifficult.

The present disclosure provides systems and methods for context rulesfor a graph. In an example, information within a graph or isolatedcollection may be adapted based on context information, including, butnot limited to, a user's location, a time (e.g., an access time, a timefor when the information will be used, etc.), a type of application orservice, a role of a user within a team or organization, environmentalconditions, security parameters, a domain associated with theinformation, among other identified, generated, and/or user-providedcontext parameters. The information may be adapted by generating acontext association between one or more rules of the isolated collection(e.g., asserted or inferred rules used to represent or generateresources, relationships, etc.) and one or more contexts to which theyshould be applied. As an example, an “at” relationship indicating a anevent is “at” a certain time (e.g., such that an event resource withinan isolated collection may be related to a time resource using an “at”relationship) may be determined to be relevant in a context where a useris reviewing a calendar or scheduling a meeting. By contrast, the “at”relationship may not be relevant or may not provide useful or actionableinformation when the user is finalizing a guest list for the event sothat a final headcount may be determined. As a result, by associatingcontext information with rules applied to an isolated collection,information within the isolated collection may be adapted based on thecontext to emphasize or make more easily accessible information that isrelevant or actionable. As will be appreciated, a rule may be appliedbased on context for any of a variety of reasons, including to limitaccess to information, to omit or deemphasize unrelated or extraneousinformation, or to generate one or more different views for theunderlying information, among other reasons.

In some examples, a graph or isolated collection may be comprised ofresources and relationships. A resource may be a document, informationrelating to a document (e.g., a revision, a comment or annotation,metadata, properties, etc.), a message, a conversation, a presenceupdate or indication, a calendar event, a user resource comprisinginformation relating to a user (e.g., a username, a user identity, anemail address, a phone number, etc.), among others. A document maycontain any kind of information, including, but not limited to, textdata, image or video data, audio data, drawings, simulations, 3D models,cryptographic keys, shared secrets, calculations, algorithms, recipes,formulas, or any combination thereof. In some examples, a resource maybe identified by a resource identifier, which may be a durable UniformResource Identifier (URI) pointing to the particular resource. Theresource identifier may also be a uniform resource locator (URL),uniform resource name (URN), or other suitable identifier or pointerspointing to the resource itself. In one example, the resource may bestored within an isolated collection. In another example, the resourcemay be stored in a data collection, while an associated resourceidentifier may be stored in an isolated collection. For example, theresource may reside on a remote server, and the resource identifier maybe used to retrieve the resource (e.g., the resource may be stored on aremote web server, where the resource identifier comprises a URL).Identifying the location of a resource may include parsing the resourceidentifier using, for example, regular expressions, providing one ormore portions of the resource identifier to a search utility, executingthe resource identifier, etc. Relationships within the isolatedcollection may identify a correlation between two or more resources inthe isolated collection. In some examples, an isolated collection may bea plurality of universal data nodes (UDNs), a document graph, or othercollection of resources and relationships.

The resources, or resource identifiers, and/or relationships may beprovided by a developer or other external source. Such resources,resources identifiers, and relationships are referred to herein asasserted resources, asserted resource identifiers, and assertedrelationships. Each isolated collection may also be enriched to createadditional relationships and in some examples additional resourceidentifiers, by executing a ruleset against the data already in theisolated collection. The additional data generated through execution ofsuch a ruleset is referred to herein as inferred data, such as inferredrelationships, inferred resources, and inferred resource identifiers.Queries may then be executed against the isolated collection thatincludes both the asserted data and inferred data to provide richerresults than would otherwise be available solely from the asserted dataalone. The isolated collection may also be stored as graph database, andresults to queries of the isolated collection may be displayed in agraphical format wherein resources are displayed as nodes and therelationships are displayed as edges, among other display formats (e.g.,as a tree, a directed graph, a matrix, a table, etc.). As used herein,an isolated collection of resource identifiers and the relationshipsbetween those resources or resource identifiers may be referred as a“Set.” Further, access to the isolated collection may be controlledthrough various techniques to provide additional security measures forthe content in each isolated collection, and each isolated collectionmay have different rule sets to generate unique and different inferreddata to meet the particular needs of each application.

In an example, one or more rules of an isolated collection may relate torelationships, resources, and/or resource identifiers that are relatedto one or more contexts. A context may be comprised of one or moreparameters, including, but not limited to, a location, a time or date,an event, a user, or a requesting application or service. In someexamples, the context may be based on a state of the isolated collectionor other information in or associated with the isolated collection. Insome examples, the context may be positively associated with the one ormore rules of the isolated collection such that the isolated collectionmay be adapted to the context when the context parameters are present orsatisfied. In other examples, a negative association may be generated,such that the rule is not applied when the context is determined. Inanother example, the rule may be emphasized or deemphasized within theisolated collection when the context is determined. As will beappreciated, any of a variety of actions may occur with respect to arule or other information of an isolated collection based on anassociation with a context and/or context parameter. As such, theinformation of the isolated collection may be adapted based on one ormore context associations.

An adaptation or representation of an isolated collection generated as aresult of evaluating a context association may be stored in orassociated with the isolated collection, may be generated dynamically(e.g., when the data is accessed, queried, etc.), or stored separatefrom the isolated collection, among other techniques. In some examples,one or more context associations may be applied to information in anisolated collection in order to determine how the context associationsmay affect at least a subpart of the isolated collection when viewed ina given context. In other examples, a context association may be revised(e.g., by adding or removing a context parameter, by modifying a contextparameter, etc.) in order to refine or iterate on the contextassociations applied to the isolated collection. In some examples,different context associations or context parameters may apply todifferent rules of an isolated collection.

A context association may be generated or provided by a user or clientof an isolated collection. In another example, a context association maybe generated automatically based on an identified behavior, requestpattern, or information structure or domain, among other factors. Insome examples, a context association may be generated or provided by anapplication or service, such that information of users of the servicemay be adapted based on the context association. In an example, a useror client may provide or generate one or more context parameters thatmay be used when adapting information in an isolated collection based ona context association. In another example, one or more contextparameters may be determined or generated automatically, which may thenbe used to adapt the information in the isolated collection. As anexample, one or more context parameters may be provided as part of arequest for information from an isolated collection (e.g., a user'slocation, information about the requesting application, etc.), whileother context parameters may be automatically generated based on thetime the request was received, the information to which the requestrelates, etc.

FIG. 1 illustrates an overview of an example system for generating,applying, and/or managing a context rule for an isolated collection.Example system 100 may be a combination of interdependent componentsthat interact to form an integrated whole for performing aspectsdisclosed herein. In aspects, system 100 may include hardware components(e.g., used to execute/run operating system (OS)), and/or softwarecomponents (e.g., applications, application programming interfaces(APIs), modules, virtual machines, runtime libraries, etc.) running onhardware. In particular aspects, system 100 may provide an environmentfor software components to execute, evaluate operational constraintsets, and utilize resources or facilities of the system 100. In suchaspects, the environment may include, or be installed on, one or moreprocessing devices. For instance, software (e.g., applications,operational instructions, modules, etc.) may be run on a processingdevice such as a computer, mobile device (e.g., smartphone/phone,tablet, laptop, personal digital assistant (PDA), etc.) and/or any otherelectronic device. As an example of a processing device operatingenvironment, refer to the exemplary operating environments depicted inFIGS. 10-13. In other instances, the components of systems disclosedherein may be distributed across and executable by multiple devices. Forexample, input may be entered on a client device and information may beprocessed or accessed from other devices in a network (e.g. serverdevices, network appliances, other client devices, etc.).

As presented, system 100 comprises client devices 102A-C, distributednetwork 104, and a distributed server environment comprising one or moreservers, such as server devices 106A-C. One of skill in the art willappreciate that the scale of systems such as system 100 may vary and mayinclude additional or fewer components than those described in FIG. 1.In some aspects, interfacing between components of the system 100 mayoccur remotely, for example, where components of system 100 may bedistributed across one or more devices of a distributed network.

In aspects, client devices 102A-C may be configured to receive input viaa user interface component or other input means. Examples of input mayinclude voice, visual, touch and text input. The interface component mayenable the creation, modification and navigation of various data setsand graphical representations. In examples, the various datasets maycomprise (or be otherwise associated with), for example, resourceidentifiers, resource metadata, relationship information, assertedrelationships, graphical mapping information, query data, rule sets,such as, for example, inference rules, authorization information,authentication information, etc., as discussed in further detail below.Generally, the datasets are stored on one or more server devices 106A-Cand are accessible by the client devices 102A-C. In some examples,however, the datasets may be at least partially stored on one or more ofthe client devices 102A-C. The underlying resources represented in thevarious datasets may be stored locally or in a data store, such as acloud storage application, accessible to client devices 102A-C. In atleast one example, the underlying resources represented in the variousdatasets (or portions thereof) may be distributed across client devices102A-C. For instance, client device 102A (e.g., a mobile phone) maylocally store a first portion of the resources represented in thedataset, client device 102B (e.g., a tablet) may locally store a secondportion of the resources, and client device 102C (e.g., a laptop) maylocally store the remaining portion of the resources represented in thedataset. In examples, the client devices 102A-C may have access to allof the resources included in the data set, may have access to a subsetof the resources included in the dataset, or, alternatively, may nothave access to any of the resources included in the dataset.

Client devices 102A-C may be further configured to interrogate datastores comprising the resources corresponding to the resourceidentifiers in the various data sets. In examples, client devices 102A-Cmay interrogate content providers, such as server device 102A-C, viadistributed network 104. The interrogation may include identifying theremote device on which a resource is located, and/or determining whetherthe remote device (or a service/separate remote device) hasauthenticated access to the resource. If access to the resource has beenauthenticated, client devices 102A-C may retrieve an authenticationindication from the remote device. Client devices 102A-C may use theauthentication indication to provide access to one or more of thevarious datasets comprising the corresponding resource identifier.

Server devices 106A-C may be configured to store and/or provide accessto one or more resources. For example, server device 102A may be a webserver, server device 102B may be a device comprising a collaborativemessaging tool and a calendaring application, and server device 102C maybe electronic mail server. Each of these devices may comprise arepository of resources that is accessible via one or moreauthentication mechanisms. In examples, server devices 106A-C mayperform or monitor the authentication process when a request for aresource is received. If the authentication is successful, theauthenticating device may store or maintain an authentication indicationfor a specified period of time. When the period of time expires, serverdevices 106A-C may remove or attempt to renew the authenticationindication. In examples, server devices 106A-C may provide theauthentication indication to an interrogating client device. In someaspects, server devices 106A-C may further be configured to store atleast a portion of the various data sets and graphical representations,as discussed above.

FIG. 2 illustrates an overview of an example system 200 for managingisolated collections of resource identifiers and correspondingrelationships. The isolated collection techniques implemented in system200 may comprise or be associated with one or more of the techniquesdescribed in FIG. 1. In alternative examples, a single device(comprising one or more components such as processor and/or memory) mayperform the processing described in systems 100 and 200, respectively.

With respect to FIG. 2, system 200 may comprise Set creationapplications 202 and 204, Set environment 206, Sets 208 and 210,entities 212 and 214, resources identifiers 216, 218, 220, 222, 224 and226, and resources 228, 230, 232, 234, 236 and 238. In aspects, Setcreation applications 202 and 204 may be an application or serviceconfigured to create, infer, manipulate, navigate and visualize variousresources, relationships and graphical representations. Set creationapplications 202 and 204 may define collections of relationships betweenresources (e.g., people, files, tasks, mail, documents, calendar events,etc.) and executing queries on those collections. Set creationapplications 202 and 204 may further provide for defining and storingrulesets used to infer one or more relationships in the collections, anddisplaying graphical representations of the collection data. The definedrulesets may be stored in the Set itself, and in some examples is storedas metadata within the Set. In examples, Set creation applications 202and 204 may be installed and executed on a client device or on one ormore devices in a distributed environment. For instance, Set creationapplication 202 may be installed on client device 102A, Set creationapplication 204 may be installed on client device 102B, and a Setcreation service associated with server device 106A may be accessible toclient device 102C.

In aspects, Set creation applications 202 and 204 may have access to afile directory or an execution environment, such as environment 206.Environment 206 may be collocated with a Set creation application, orenvironment 206 may be located remotely from the Set creationapplication. Environment 206 may provide access to one or more datacollections, such as Sets 208 and 210. In examples, access to the datacollections may be determined using one or more sets of permissionsgenerated and/or maintained by Set creation applications 202 and 204.The sets of permissions may be different across one or more of the datacollections. As a result, one or more of the data collections (orfunctionality associated therewith) may not be accessible from one ormore of Set creation applications 202 and 204.

Sets 208 and 210 may respectively comprise isolated collections ofasserted resource identifiers and corresponding relationships. Therelationships in the isolated collections may be defined manually or maybe automatically derived using one or more rulesets. The isolatedcollections may be represented using graphical structures that directlyrelate resources in the data collection and provide for retrievingrelationship data with a single operation. Each isolated collection maycomprise resource identifiers that are unique to that isolatedcollection. Alternately, the isolated collections may comprise resourceidentifiers included in one or more alternate isolated collections. Forexample, as depicted in FIG. 2, Set 208 may comprise resourceidentifiers 216, 218, 220 and 222, and Set 210 may comprise resourceidentifiers 220, 222, 224 and 226. Resource identifiers 216, 218, 220,222, 224 and 226 may correspond to, and/or identify the location of, oneor more resources. As used herein, a resource identifier references anexisting resource, but is not itself a resource. Exemplary types ofresource identifiers include, but are not limited to, a Uniform ResourceIdentifier (e.g., a Uniform Resource Locator (URL), a Uniform ResourceName (URN) etc.), an IP address, a memory or storage address, and thelike. One of skill in the art will appreciate that any type ofidentifier may be employed by the various aspects disclosed hereinwithout departing from the scope of this disclosure. Identifying thelocation of a resource may include parsing the resource identifierusing, for example, regular expressions, providing one or more portionsof the resource identifier to a search utility, executing the resourceidentifier, etc. In aspects, having access to the data collections doesnot guarantee access to the resources identified by the resourceidentifiers included in each data collection. For example, although auser may be able to access and manipulate Set 208, the user may not beauthorized to access one or more of the underlying resourcescorresponding to the resource identifier in Set 208.

Resource providers 212 and 214 may be configured to store and/or provideaccess to one or more resources. As such, a resource provider as usedherein may be a data store, a cloud service provider, a client computingdevice, a server computing device, a distributed system of devices, suchas, for example, an enterprise network, an application, a softwareplatform (e.g., an operating system, a database, etc.), and the like. Inaspects, resource providers 212 and 214 may be (or have access to)various different data sources, such as content providers, data stores,various sets of application data, and the like. The data stores maycomprise one or more resources corresponding to one or more resourceidentifiers. For example, as depicted in FIG. 2, resource provider 212may be a data store comprising various different types of resources suchas resource 228 (e.g., document 1 (D1)) and resource 230 (e.g.,presentation 2 (P1)) and resource provider 214 may be a contactmanagement application comprising contact resources 232 (e.g., contact 1(C1)), 234 (e.g., contact 2 (C2)), 236 (e.g., contact 3 (C3)) and 238(e.g., contact 4 (C4)). In this example, resource identifier 216 maycorrespond to resource 228; resource identifier 218 may correspond toresource 230; resource identifier 220 may correspond to resource 232;resource identifier 222 may correspond to resource 234; resourceidentifier 224 may correspond to resource 236; and resource identifier226 may correspond to resource 238. In some aspects, resource providers212 and 214 may be accessible by Set creation applications 202 and 204.Set creation applications 202 and 204 may access resource providers 212and 214 to determine the existence of resources and/or retrieveinformation associated with the resources (e.g., resource metadata,resource location, resource identifiers, permission sets, authenticationdata, etc.). The information retrieved from resource providers 212 and214 may be used to determine a set of resource identifiers correspondingto one or more of the available resources. The set of resourceidentifiers may be used to create one or more isolated collections ofasserted resource identifiers and corresponding relationships. As notedabove, the resource identifiers may be, or include, a durable URI forits corresponding resource. For instance, the resource identifier 216may include the URI for the actual document (D1) 228. Accordingly, insuch an example, a user is able to determine the location of thedocument (D1) 228 from the Set, and, depending on authentication andaccess restrictions, retrieve the document (D1) 228. As another example,as depicted in FIG. 2, resource provider 212 may be accessed by Setcreation application 202. Set creation application 202 may determinethat resource provider 212 comprises at least resources 228 and 230, andmay determine resource identification information for each of theresources. Based on the determined resource identification information,resource identifiers 216 and 218 may be respectively applied/correlatedto resources 228 and 230, and provided to environment 206. Environment206 may then make resource identifiers 216 and 218 eligible for aninclusion analysis into one or more isolated collections.

FIG. 3A illustrates an example isolated collection 300 of assertedresource identifiers and corresponding relationships. Example isolatedcollection 300 comprises resource identifiers 302, 304, 306, 308, 310,312 and 314, and relationships 316, 318, 320, 322, 324 and 326. Inaspects, isolated collection 300 may be generated and/or manipulatedusing a collection creation utility that may be included as part of aSet creation application as discussed above. When presented in graphform as depicted in the FIG. 3A, each resource identifier may bereferred to as a “node” and each relationship may be referred to as an“edge.” The collection creation utility may also identify resourcesand/or determine resource types for collections using one or morerulesets that may include rules defined in accordance with semantic webtechnologies, such as resource description framework (RDF), RDF schema(RDFS), SPARQL Protocol and RDF Query Language (SPARQL), Web OntologyLanguage (OWL), etc. For example, collection 300 includes a resourceidentifier 312 that represents an underlying resource, “email789” in thedepicted example. Similarly, resource identifier 304 represents aresource document, “Doc123,” and resource identifier 302 represents aresource task, “Task123.” Each of the resources and relationshipsincluded in the isolated collection 300 may have been asserted by adeveloper through a Sets creation application. For instance, a developermay manually add each of the resource identifiers and the relationshipsbetween the resource identifiers. As an example, the developer maymanually indicate that the “task123” is a task on “Doc123,” asrepresented in the collection 300 by the “taskOn” relationship 316. Theresource identifiers and relationships may also be asserted by anexternal bot or application created by a developer. For instance, anadd-in may be programmed to monitor activity in a browser or otherapplication to track usage of the application. Based on the usage of theapplication, the add-in sends additional resources and relationships tobe included in the collection 300.

In contrast to the asserted resource identifiers and relationships, acollection creation utility may execute a ruleset to determineadditional relationships and resource types, referred to herein as“inferred relationships” and “inferred resource identifiers” or“inferred resource types.” For example, upon execution of a ruleset, thecollection creation utility may determine that resource identifier 312represents an email message, and resource identifier 304 represents adocument. Generation of inferred relationships and resources isdiscussed in further detail below.

Isolated collection 300 further depicts that resource identifier 302 isassociated with resource identifiers 304, 306 and 308 and resourceidentifier 310. The collection creation utility may determine that theresource identifier 302 represents a task to be performed on identifiers304, 306, and 308. Based on this determination, the collection creationutility may assign relationships 316, 318 and 320 (e.g., “taskOn”) todefine the association between resource identifier 302 and resourceidentifier 304, 306 and 308. In other examples, the relationships 316,318, and 320 may be asserted, as discussed above. Additionalrelationships, such as the “hasDiscussion” relationship 322 may havebeen asserted manually by a developer or asserted from an add-in of ane-mail application that analyzed the content of e-mail 101. Whilespecific types of resources and relationships are described in FIG. 3A,one of skill in the art will appreciate that other types of resourcesand/or relationships may be included in an isolated collection withoutdeparting from the spirit of this disclosure.

FIGS. 3B-3E illustrate an example query model that may be used totraverse collection 300. In aspects, queries may be executed via aninterface provided by the collection creation utility. A query may beexecuted against one or more files and/or directories comprisinginformation, such as resource identifiers, resource type, resourcemetadata, permission data, etc. The query results may be visualized in agraph form as one or more collections, such as collection 300. Forexample, the entire collection 300 dataset may comprise only thoseelements illustrated in collection 300 (e.g., resource identifiers 302,304, 306, 308, 310, 312 and 314 and relationships 316, 318, 320, 322,324 and 326). In this particular example, resource identifier 312 mayrepresent an email comprising the subject “API Design” and resourceidentifier 314 may represent an email comprising the subject “Sets.” Thequery ‘http:// . . . /collection300/task123’ may be executed againstcollection 300. The query results may comprise resource identifier 302and be visualized as illustrated in FIG. 3B. In FIG. 3C, the query hasbeen amended to ‘http:// . . . /collection300/task123?$expand=taskOn’and executed against collection 300. The query results may compriseresource identifiers 302, 304, 306 and 308 and relationships 316, 318and 320, and be visualized as illustrated in FIG. 3C. In FIG. 3D, thequery has been amended to ‘http:// . . ./collection300/task123?$expand=taskOn($expand=attachmentOn)’ andexecuted against collection 300. The query results may comprise resourceidentifiers 302, 304, 306, 308, 312 and 314 and relationships 316, 318,320, 324 and 326, and be visualized as illustrated in FIG. 3D. In FIG.3E, the query has been amended to http:// . . ./collection300/task123?($expand=taskOn($expand=attachmentOn)($filter=Subjecteq ‘Sets’))′ and executed against collection 300. As only resourceidentifier comprises 314 the subject “Sets”, the query results maycomprise resource identifiers 302, 306 and 314 and relationships 318 and326, and be visualized as illustrated in FIG. 3E.

FIGS. 4A-4E illustrate overviews of an example isolated collectionaccording to aspects disclosed herein. As will be discussed in greaterdetail below, FIG. 4A illustrates information in an isolated collection400, while FIGS. 4B-4E illustrate various views or representations ofthe isolated collection in FIG. 4A based on one or more contextassociations used to adapt one or more rules.

FIG. 4A illustrates an example isolated collection 400 having aplurality of resource identifiers and relationships. As depicted invisual representation 400A, isolated collection 400 may compriseinformation relating to several people (e.g., PersonA 402, PersonB 404,and PersonC 406) and two meetings (e.g., MeetingA 408 and MeetingB 410)for which they are attendees. Beginning with MeetingA 408, PersonA 402and PersonB 404 may be attendees, as illustrated by “attendee”relationships 412 and 414. Relationships 412 and 414 may be directional,in that they indicate that the attendees of MeetingA 408 may be PersonA402 and PersonB 404, rather than the other way around. In an example,relationships 412 and 414 may use solid arrows to indicate assertedrelationships rather than relationships that may have been created byone or more inference rules. As an example, “attended” relationships 416and 418 may be illustrated using dashed arrows to indicate that the“attended” relationships between PersonA 402 and MeetingA 408, andPersonB 404 and MeetingA 408 may be inferred relationships resultingfrom the “attended inverseOf attendee” rule in rules 400B. Relationships416 and 418 may be directional, in order to indicate that PersonA 402and PersonB 404 attended MeetingA 408, rather than the other way around.

Several other resources may be related to MeetingA 408, each of whichmay provide additional information relating to MeetingA 408. In anexample, RoomA 424 may be related to MeetingA 408 by “location”relationship 426, indicating that the location of MeetingA 408 was inRoomA 424. Conversely, “hosted” relationship 428 may indicate that RoomA424 hosted MeetingA 408. Relationships 426 and 428 may be illustratedusing a solid line and a dashed line, respectively, thereby indicatingthat relationship 426 may be an asserted relationship, whilerelationship 428 may be an inferred relationship (e.g., resulting fromthe rule “hosted inverseOf location” in rules 400B). DateTimeA 420 mayprovide information relating to when MeetingA 408 occurred, and may berelated to MeetingA 408 by “at” relationship 422, indicating thatMeetingA 408 was at DateTimeA 420. Additionally, Project 430 may berelated to MeetingA 408, indicating that the topic of MeetingA 408 wasProject 430, as illustrated by “topic” relationship 432 between MeetingA408 and Project 430. Inverse “wasDiscussed” relationship 434 may existbetween Project 430 and MeetingA 408 to indicate that Project 430 wasdiscussed during Meeting 408. As above, relationships 422 and 432 may beillustrated using solid lines to indicate asserted relationships, whilerelationship 434 may be illustrated using a dashed line to indicate aninferred relationship.

Turning now to the resources and relationships associated with MeetingB410, PersonA 402, Person B 404, and PersonC 406 may be attendees ofMeetingB 410, as illustrated by “attendee” relationships 436, 438, and440 from MeetingB 410 to PersonA 402, PersonB 404, and PersonC 406,respectively. As above, relationships 436-440 may be represented usingsolid arrows to indicate that asserted directional relationships existsbetween MeetingB 410 and PersonA 402, PersonB 404, and PersonC 406.Inferred “attended” relationships 442, 444, and 446 may exist fromPersonA 402, PersonB 404, and PersonC 406 to MeetingB 410. The inferredrelationships 442-446 may be indicated using dashed lines.

Several other resources may be related to MeetingB 410, each of whichmay provide additional information relating to MeetingB 410. In anexample, RoomB 452 may be related to MeetingB 410 by “location”relationship 454, indicating that the location of MeetingB 410 was inRoomB 452. Conversely, “hosted” relationship 456 may indicate that RoomB452 hosted MeetingB 410. Relationships 454 and 456 may be illustratedusing a solid line and a dashed line, respectively, thereby indicatingthat relationship 454 may be an asserted relationship, whilerelationship 456 may be an inferred relationship (e.g., resulting fromthe rule “hosted inverseOf location” in rules 400B). DateTimeB 448 mayprovide information relating to when MeetingB 410 occurred, and may berelated to MeetingB 410 by “at” relationship 450, indicating thatMeetingB 410 was at DateTimeB 448.

As illustrated in isolated collection 400, there may be many differentresources and relationships stored in an isolated collection, not all ofwhich may be relevant or useful at any given time. While specificexamples are discussed herein with respect to FIGS. 4A-4E, it will beappreciated that an isolated collection may store any type ofinformation relating to any domain.

With respect to FIG. 4B, isolated collection 400 (e.g., visualrepresentation 400A and/or rules 400B) may be adapted based on context.As an example, isolated collection 460 (e.g., visual representation 460Aand rules 460B) may be generated as an adaptation of isolated collection400 based on a context indicating that a user (e.g., a user associatedwith a person resource such as PersonA 402) may be evaluating his or hercalendar. In some examples, the context may comprise a context parameterindicating that the user is accessing isolated collection 400 using acalendaring application such as MICROSOFT OUTLOOK or GOOGLE CALENDAR, oranother application. In other examples, the context may relate to a timethat the user typically accesses calendar data, an evaluation of whetherthe user has recently exited a meeting, a determination that anotheruser has requested meeting availability from the user, etc.

As compared between rules 400B and rules 460B, certain rules may beomitted based on applying one or more context associations to isolatedcollection 400. As illustrated, inference rules “hosted inverseOflocation” and “wasDiscussed inverseOf topic” may have been omitted dueto a negative association with the context, as such information may notbe relevant when performing a calendar evaluation. In an example, one ormore rules and/or relationships relating to “attendee” may have anegative association with the context and may be omitted from Rules460B. In another example, rules relating to PersonA 402 may bedetermined to be relevant, as PersonA 402 may be performing the calendarevaluation.

In some examples, additional rules may be positively associated with thecontext and added as a result of applying the context association, suchas “MeetingA scheduledBefore MeetingB” and “scheduledAfter inverseOfscheduledBefore,” as illustrated by relationships 462 and 464,respectively. Given that identifying an ordering for meetings may berelevant when evaluating one's calendar, such rules may be associatedwith the context. As will be appreciated, while specific examples ofpositive and negative rule associations are provided herein, such ruleassociations are examples and any of a variety of other rule types,relationships, resources, or information from other domains may be usedaccording to aspects disclosed herein without departing from the spiritof this disclosure.

FIG. 4C illustrates another example adaptation of isolated collection400 in FIG. 4A. In an example, isolated collection 470 (e.g., visualrepresentation 470A and rules 470B) may be generated based on a contextassociation indicating that a user (e.g., a user associated with aperson resource such as PersonA 402 or PersonB 404) would like to viewinformation relating to people he or she has met before (e.g., atMeetingA 408) and will meet again (e.g., at MeetingB 410). Theindication may be a result of the manner in which isolated collection400 is queried (e.g., when request was made, from which application, theuser's location, etc.) or an automatic determination (e.g., the usertypically requests a person-centric view of isolated collection 400 at agiven time, it is determined that PersonA 402 has seen PersonB 404before based on evaluating the resources and relationships in theisolated collection, or any other circumstance), among other contextparameters.

As a result of applying the context association to isolated collection400, one or more pre-existing rules of rules 400B in FIG. 4A may beomitted or modified to generate rules 470B. In another example, one ormore rules may be added. As illustrated, rules 470B comprise time andlocation information (e.g., DateTimeA 420, DateTimeB 448, RoomA 424, andRoomB 452) relating to MeetingA 408 and MeetingB 410. This informationmay be emphasized or selected from isolated collection 400 as a resultapplying the context association because the information is relevant todetermine when PersonA 402 has previously seen PersonB 404. Similarly,the inference rule “attended inverseOf attendee” and associatedrelationships 416 and 418 may be included as they are relevant toidentify which other meetings PersonB 404 attended (e.g., from MeetingB410, it may be determined that PersonB 404 was an attendee of MeetingB410 via relationship 438, such that it may then be determined thatPersonB 404 attended MeetingA 408 by way of relationship 418). Inanother example, information may be omitted or deemphasized, such as theinverse relationship “wasDiscussed inverseOf topic” and associatedrelationships 428 and 456. As compared to visual representation 400A ofisolated collection 400, visual representation 470A may comprise adifferent view of the underlying information such that relevantinformation relating to a determined context may be selected oremphasized as a result of applying one or more context associations togenerate rules 470B.

FIG. 4D illustrates another example view of isolated collection 400 inFIG. 4A. In an example, isolated collection 480 may be an adaptation ofisolated collection 400 resulting from the application of a contextassociation. The context association may be based on context parametersas discussed herein, including, but not limited to, a parameter relatingto a requestor (e.g., one or more security privileges, a user's rolewithin an organization or a multi-tenant environment, etc.), thelocation from which the request was received, a time associated with therequest (e.g., the time the request was received, the time theinformation associated with the request was updated or accessed, etc.),among other context parameters. As an example, mapping rules 480B may bean adaptation of isolated collection 400 such that information relatingto RoomA 424 is selected or emphasized. For example, it may be relevantto determine who was recently in the room, when the room was last used,or which meeting the room last hosted. A context association mayassociate a context with one or more rules as discussed herein based onthe location of the requestor (e.g., whether the client or user isrequesting information from the isolated collection is in RoomA 424),the time (e.g., it may be determined from DateTimeA 420, based on itsindirect relationship with RoomA 424, that MeetingA 408 will occur orhas occurred in RoomA 424), or any of a variety of other contextparameters.

As such, information that is not relevant may be omitted or deemphasizedin isolated collection 480 (e.g., from visual representation 480A and/orrules 480B) as a result of one or more context associations, such asresources and relationships that are not related to RoomA 424 and/orMeetingA 408 (e.g., PersonC 406, MeetingB 410, Project 430, DateTimeB448, and RoomB 452). For example, a context association may specifyrelationships and/or resource types to omit (e.g., a relationship suchas “location” relationship 426, a project resource such as Project 430,etc.). In another example, a context association may specify thatrelationships of a certain direction should be maintained (e.g.,relationships connecting resources in an isolated collection to acertain resource, such as relationships that relate other resources toRoomA 424). In some examples, a context association may specify aresource, relationship, resource type, or other information that shouldbe emphasized or selected within a graph. As an example, the contextassociation may indicate RoomA 424 and related resources and/orrelationships may be selected.

FIG. 4E illustrates another example view of isolated collection 400 inFIG. 4A. In an example, isolated collection 490 may be an adaptation ofisolated collection 400 as a result of applying one or more contextassociations. The context associations may be based on one or morecontext parameters as discussed herein. For example, isolated collection490 may be an adaptation of isolated collection 400 as a result of ascheduling context, wherein it may be determined that the information inisolated collection 400 is being accessed while attempting to identify alocation for a meeting or other event. As such, one or more contextassociations may be applied to isolated collection 400 in order togenerate isolated collection 490 and related visual representation 490Aand rules 490B.

As an example, a negative context association may exist for rulesrelating to “attendee” relationships (e.g., relationships 412, 414, 436,438, and 440), resources and/or relationships associated with “attendee”relationships (e.g., relationships resulting from the “attendedinverseOf attendee” rule in rules 402B), or project resources (e.g.,project 430). In another example, a positive context association mayexist for rules relating to relationships originating from roomresources 424 and 452, such as “hosted” inferred relationships 428 and456, respectively. As will be appreciated, inferred information (e.g.,inferred resources, inferred relationships, etc.) may remain or beemphasized in an adaptation of an isolated collection even though theasserted information to which it relates may be omitted or deemphasizedas a result of applying one or more context associations. In anotherexample, a resource type or relationship may be modified as a result ofa context association. For example, a “hosted” relationship may beadapted to a “hosting” relationship (or vice versa) based on adetermination that a DateTime resource indicates a meeting time that isin the future. It will be appreciated that a context association mayspecify any of a variety of context parameters, as discussed herein, andmay comprise logic used to evaluate the context parameters, which may bebased on other internal or external information.

FIG. 5 illustrates an overview of an example method 500 for adapting anisolated collection based on context information. Method 500 may beperformed by one or more computing devices, such as client devices102A-C and/or server devices 106A-C in FIG. 1. Method 500 begins atoperation 502, where a request for information in an isolated collectionmay be received. The request may be received from a user of the isolatedcollection, from a client accessing, interacting with, or storinginformation in the isolated collection, or an application or service,among other requestors. The request may be a query for targetinformation in the isolated collection (e.g., using a query languagesuch as Cypher Query Language or SPARQL Protocol and RDF QueryLanguage), may comprise a reference to one or more references toresources and/or relationships within the isolated collection (e.g.,based on a unique resource identifier, a specific characteristic orproperty, or other identifying information), among other types ofrequests.

At operation 504, a context associated with the request may be received.In an example, the context may be received from the requestor (e.g.,from an application, a user device, etc.). In another example, thecontext may be generated or accessed from internal and/or externalinformation (e.g., a time or date, a state of the isolated collection,security information relating to the request or requestor, etc.). Thecontext may comprise one or more context parameters as disclosed herein.As an example, context may be determined based on the request, such as atype of user making the request (e.g., the role of the user, the user'stitle or job within an organization, etc.), the type of application usedto provide the request (e.g., whether the application is part of aproductivity suite, whether the application is a specific application,whether the application is up to date, etc.), or other information orattributes that may be determined or generated based on the request(e.g., an originating location, a request size, whether the request is arefinement of a previous request, etc.). As will be appreciated, contextinformation relating to one or more context parameters may be generated,received, or accessed from any of a variety of sources and/or based onany internal or external information without departing from the spiritof this disclosure.

Moving to operation 506, one or more rules associated with the isolatedcollection may be accessed. The rules may comprise asserted rules (e.g.,relating to asserted resources, asserted relationships, etc.), inferencerules (e.g., relating to inferred resources, inferred relationships,etc.), context associations, among other rules. The rules may be storedin the isolated collection, associated with the isolated collection, orstored as a separate ruleset. In some examples, the rules may be storedusing the same computing device or storage system as is used to providethe isolated collection, or may be stored using a different computingdevice or storage system. Accessing the rules may comprise providing atleast a part of the context received in operation 504, or may compriseretrieving a subpart of rules in a ruleset. In an example, one or morecontext associations may be associated with each rule and/or ruleset. Inanother example, the context associations may be stored separately fromthe rules and/or rulesets to which they apply. While specific examplesare discussed herein with respect to generating an association between arule and a context to form a context association, it will be appreciatedthat generating and/or storing a context association may be achievedusing any of a variety of techniques.

At operation 508, the rules may be adapted based on the receivedcontext. In an example, one or more context associations may beevaluated based on the context in order to adapt the rules to thereceived context. Adapting the rules may comprise iterating through theaccessed rules to determine whether any applicable context associationsapply to one or more of the rules (e.g., whether a rule is associatedwith a context association or whether a context association specifieslogic that may be applied to a rule, among other examples). For example,a rule may have a property, attribute, or metadata indicating that oneor more contexts are associated with the rule. In an example, theassociated context may comprise an association type (e.g., a positiveassociation, a negative association, an emphasis or de-emphasisassociation, etc.). In another example, one or more context associationsmay be evaluated in order to identify rules to which the contextassociations relate. In another example, adapting the rules based on thereceived context may comprise modifying or omitting a pre-existing ruleand/or generating a new rule. In some examples, a combination oftechniques may be used when adapting the rules. In other examples, oneor more rules of the accessed rules may remain unchanged as a result ofdetermining there is a positive context association, no contextassociation, or other indications.

When adapting the rules, the context (e.g., one or more contextparameters) may be evaluated using the context association. For example,a context parameter may indicate a device location, such that alocation, region, or other geographical information comprised by acontext association may be compared to or evaluated based on theindicated device location. In another example, a context parameter mayspecify an isolated collection state or condition, such that, whenevaluating the context association, the isolated collection may beaccessed or queried in order to determine whether the isolatedcollection exhibits the specified state. In some examples, evaluating acontext association may comprise accessing or retrieving additionalinformation (e.g., from an application, a computing device, a storagesystem, a website, etc.). In other examples, the context association maycomprise logic, indicating that one or more of the context parametersshould be satisfied, multiple parameters should be satisfied, oneparameter should be satisfied if another parameter is satisfied, etc. Aswill be appreciated, a context association may specify any of a varietyof logic clauses, structures, or algorithms. Similarly, a contextassociation may relate to a wide array of context information and/orcontext parameters.

Moving to operation 510, a response may be generated from the isolatedcollection using the adapted rules. Generating the response may compriseomitting resources and/or relationships from the response or modifyingand/or creating resources and/or relationships, among other operations.In an example, the response may comprise at least a subpart of theisolated collection. In another example, the response may comprise atleast a subpart of the adapted rules. In some examples, the response maycomprise intermediate information that was generated based on thecontext or as a result of evaluating one or more context associations.The response may be provided in any of a variety of formats, including,but not limited to, as a subpart of an isolated collection, as aJavaScript Object Notation (JSON) object, or as a table or spreadsheetdocument, or any combination thereof. In some examples, information thatwas omitted or deemphasized at operation 508 may be provided (e.g., as aseparate object, as part of the results, etc.).

At operation 512, the generated response may be provided. The responsemay be provided as a response to the request, using a callback function,as a separate electronic transmission, among other techniques. In someexamples, the response may be provided for further evaluation of anothercontext association, such that a context association may be dependent onthe result of one or more other context associations. Flow terminates atoperation 512.

FIG. 6 illustrates an overview of an example method 600 for generating acontext association for an isolated collection. Method 600 may beperformed by one or more computing devices, such as client devices102A-C and/or server devices 106A-C in FIG. 1. In an example, method 600may be performed at the request of a user or client, or may be performedautomatically (e.g., as a result of identifying a context association,when a rule is added to an isolated collection, etc.). Method 600 beginsat operation 602, where one or more rules associated with an isolatedcollection may be accessed. In some examples, the rules may be provided(e.g., by a user, a client, etc.) or accessed (e.g., from the isolatedcollection, from a storage system, from a computing device, from anisolated collection or data store associated with a user, etc.).

At operation 604, one or more context parameters may be determined asassociated with a context. Determining the context parameters maycomprise receiving a context parameter (e.g., from a user, a client, anapplication, a user device, etc.), generating a context parameter (e.g.,by performing pattern analysis to identify a pattern of behavior, as aresult of using machine learning to identify an association, etc.), orany combination thereof. In some examples, multiple context parametersrelating to one or more contexts may be received and/or generated. Acontext may comprise logic relating to one or more context parameters,external or internal information, algorithms, or other logic.

Moving to operation 606, a context association may be generated betweenthe parameter and one or more of the rules. Generating the contextassociation may comprise associating one or more of the rules with thecontext (e.g., based on a unique identifier, based on one or moreresources and/or relationships to which they relate, etc.), associatingthe context with one or more of the rules (e.g., by modifying a rule torelate to the context, to have metadata associated with the context,etc.), or any combination thereof. As will be appreciated any of avariety of techniques may be used to generate the context association soas to associate one or more of the rules with the context.

At operation 608, the context association may be associated with theisolated collection. In an example, the context association may beassociated with the isolated collection, stored using the isolatedcollection, or stored using a storage system. In another example, thecontext association may be stored such that it is specific to a user,client, or application, etc. to which it relates, rather than beingapplied or associated with the isolated collection as a whole. In someexamples, the context association may be stored by a user device orassociated with a client or other application, such that the adaptationmay be performed locally rather than performed by the isolatedcollection, storage system, or computing device. While specific examplesare discussed herein, it will be appreciated that the contextassociation may be stored or associated using any of a variety oftechniques without departing from the spirit of this disclosure. Flowterminates at operation 608.

FIGS. 7-10 and the associated descriptions provide a discussion of avariety of operating environments in which aspects of the disclosure maybe practiced. However, the devices and systems illustrated and discussedwith respect to FIGS. 7-10 are for purposes of example and illustrationand are not limiting of a vast number of computing device configurationsthat may be utilized for practicing aspects of the disclosure, describedherein.

FIG. 7 is a block diagram illustrating physical components (e.g.,hardware) of a computing device 700 with which aspects of the disclosuremay be practiced. The computing device components described below may besuitable for the computing devices described above. In a basicconfiguration, the computing device 700 may include at least oneprocessing unit 702 and a system memory 704. Depending on theconfiguration and type of computing device, the system memory 704 maycomprise, but is not limited to, volatile storage (e.g., random accessmemory), non-volatile storage (e.g., read-only memory), flash memory, orany combination of such memories. The system memory 704 may include anoperating system 705 and one or more program modules 706 suitable forperforming the various aspects disclosed herein such as contextassociation generation component 724 and isolated collection adaptationcomponent 726. The operating system 705, for example, may be suitablefor controlling the operation of the computing device 700. Furthermore,embodiments of the disclosure may be practiced in conjunction with agraphics library, other operating systems, or any other applicationprogram and is not limited to any particular application or system. Thisbasic configuration is illustrated in FIG. 7 by those components withina dashed line 708. The computing device 700 may have additional featuresor functionality. For example, the computing device 700 may also includeadditional data storage devices (removable and/or non-removable) suchas, for example, magnetic disks, optical disks, or tape. Such additionalstorage is illustrated in FIG. 7 by a removable storage device 709 and anon-removable storage device 710.

As stated above, a number of program modules and data files may bestored in the system memory 704. While executing on the processing unit702, the program modules 706 (e.g., application 720) may performprocesses including, but not limited to, the aspects, as describedherein. Other program modules that may be used in accordance withaspects of the present disclosure may include electronic mail andcontacts applications, word processing applications, spreadsheetapplications, database applications, slide presentation applications,drawing or computer-aided application programs, etc.

Furthermore, embodiments of the disclosure may be practiced in anelectrical circuit comprising discrete electronic elements, packaged orintegrated electronic chips containing logic gates, a circuit utilizinga microprocessor, or on a single chip containing electronic elements ormicroprocessors. For example, embodiments of the disclosure may bepracticed via a system-on-a-chip (SOC) where each or many of thecomponents illustrated in FIG. 7 may be integrated onto a singleintegrated circuit. Such an SOC device may include one or moreprocessing units, graphics units, communications units, systemvirtualization units and various application functionality all of whichare integrated (or “burned”) onto the chip substrate as a singleintegrated circuit. When operating via an SOC, the functionality,described herein, with respect to the capability of client to switchprotocols may be operated via application-specific logic integrated withother components of the computing device 700 on the single integratedcircuit (chip). Embodiments of the disclosure may also be practicedusing other technologies capable of performing logical operations suchas, for example, AND, OR, and NOT, including but not limited tomechanical, optical, fluidic, and quantum technologies. In addition,embodiments of the disclosure may be practiced within a general purposecomputer or in any other circuits or systems.

The computing device 700 may also have one or more input device(s) 712such as a keyboard, a mouse, a pen, a sound or voice input device, atouch or swipe input device, etc. The output device(s) 714 such as adisplay, speakers, a printer, etc. may also be included. Theaforementioned devices are examples and others may be used. Thecomputing device 700 may include one or more communication connections716 allowing communications with other computing devices 750. Examplesof suitable communication connections 716 include, but are not limitedto, radio frequency (RF) transmitter, receiver, and/or transceivercircuitry; universal serial bus (USB), parallel, and/or serial ports.

The term computer readable media as used herein may include computerstorage media. Computer storage media may include volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information, such as computer readableinstructions, data structures, or program modules. The system memory704, the removable storage device 709, and the non-removable storagedevice 710 are all computer storage media examples (e.g., memorystorage). Computer storage media may include RAM, ROM, electricallyerasable read-only memory (EEPROM), flash memory or other memorytechnology, CD-ROM, digital versatile disks (DVD) or other opticalstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, or any other article of manufacturewhich can be used to store information and which can be accessed by thecomputing device 700. Any such computer storage media may be part of thecomputing device 700. Computer storage media does not include a carrierwave or other propagated or modulated data signal.

Communication media may be embodied by computer readable instructions,data structures, program modules, or other data in a modulated datasignal, such as a carrier wave or other transport mechanism, andincludes any information delivery media. The term “modulated datasignal” may describe a signal that has one or more characteristics setor changed in such a manner as to encode information in the signal. Byway of example, and not limitation, communication media may includewired media such as a wired network or direct-wired connection, andwireless media such as acoustic, radio frequency (RF), infrared, andother wireless media.

FIGS. 8A and 8B illustrate a mobile computing device 800, for example, amobile telephone, a smart phone, wearable computer (such as a smartwatch), a tablet computer, a laptop computer, and the like, with whichembodiments of the disclosure may be practiced. In some aspects, theclient may be a mobile computing device. With reference to FIG. 8A, oneaspect of a mobile computing device 800 for implementing the aspects isillustrated. In a basic configuration, the mobile computing device 800is a handheld computer having both input elements and output elements.The mobile computing device 800 typically includes a display 805 and oneor more input buttons 810 that allow the user to enter information intothe mobile computing device 800. The display 805 of the mobile computingdevice 800 may also function as an input device (e.g., a touch screendisplay). If included, an optional side input element 815 allows furtheruser input. The side input element 815 may be a rotary switch, a button,or any other type of manual input element. In alternative aspects,mobile computing device 800 may incorporate more or less input elements.For example, the display 805 may not be a touch screen in someembodiments. In yet another alternative embodiment, the mobile computingdevice 800 is a portable phone system, such as a cellular phone. Themobile computing device 800 may also include an optional keypad 835.Optional keypad 835 may be a physical keypad or a “soft” keypadgenerated on the touch screen display. In various embodiments, theoutput elements include the display 805 for showing a graphical userinterface (GUI), a visual indicator 820 (e.g., a light emitting diode),and/or an audio transducer 825 (e.g., a speaker). In some aspects, themobile computing device 800 incorporates a vibration transducer forproviding the user with tactile feedback. In yet another aspect, themobile computing device 800 incorporates input and/or output ports, suchas an audio input (e.g., a microphone jack), an audio output (e.g., aheadphone jack), and a video output (e.g., a HDMI port) for sendingsignals to or receiving signals from an external device.

FIG. 8B is a block diagram illustrating the architecture of one aspectof a mobile computing device. That is, the mobile computing device 800can incorporate a system (e.g., an architecture) 802 to implement someaspects. In one embodiment, the system 802 is implemented as a “smartphone” capable of running one or more applications (e.g., browser,e-mail, calendaring, contact managers, messaging clients, games, andmedia clients/players). In some aspects, the system 802 is integrated asa computing device, such as an integrated personal digital assistant(PDA) and wireless phone.

One or more application programs 866 may be loaded into the memory 862and run on or in association with the operating system 864. Examples ofthe application programs include phone dialer programs, e-mail programs,personal information management (PIM) programs, word processingprograms, spreadsheet programs, Internet browser programs, messagingprograms, and so forth. The system 802 also includes a non-volatilestorage area 868 within the memory 862. The non-volatile storage area868 may be used to store persistent information that should not be lostif the system 802 is powered down. The application programs 866 may useand store information in the non-volatile storage area 868, such ase-mail or other messages used by an e-mail application, and the like. Asynchronization application (not shown) also resides on the system 802and is programmed to interact with a corresponding synchronizationapplication resident on a host computer to keep the information storedin the non-volatile storage area 868 synchronized with correspondinginformation stored at the host computer. As should be appreciated, otherapplications may be loaded into the memory 862 and run on the mobilecomputing device 800 described herein (e.g., search engine, extractormodule, relevancy ranking module, answer scoring module, etc.).

The system 802 has a power supply 870, which may be implemented as oneor more batteries. The power supply 870 might further include anexternal power source, such as an AC adapter or a powered docking cradlethat supplements or recharges the batteries.

The system 802 may also include a radio interface layer 872 thatperforms the function of transmitting and receiving radio frequencycommunications. The radio interface layer 872 facilitates wirelessconnectivity between the system 802 and the “outside world,” via acommunications carrier or service provider. Transmissions to and fromthe radio interface layer 872 are conducted under control of theoperating system 864. In other words, communications received by theradio interface layer 872 may be disseminated to the applicationprograms 866 via the operating system 864, and vice versa.

The visual indicator 820 may be used to provide visual notifications,and/or an audio interface 874 may be used for producing audiblenotifications via the audio transducer 825. In the illustratedembodiment, the visual indicator 820 is a light emitting diode (LED) andthe audio transducer 825 is a speaker. These devices may be directlycoupled to the power supply 870 so that when activated, they remain onfor a duration dictated by the notification mechanism even though theprocessor 860 and other components might shut down for conservingbattery power. The LED may be programmed to remain on indefinitely untilthe user takes action to indicate the powered-on status of the device.The audio interface 874 is used to provide audible signals to andreceive audible signals from the user. For example, in addition to beingcoupled to the audio transducer 825, the audio interface 874 may also becoupled to a microphone to receive audible input, such as to facilitatea telephone conversation. In accordance with embodiments of the presentdisclosure, the microphone may also serve as an audio sensor tofacilitate control of notifications, as will be described below. Thesystem 802 may further include a video interface 876 that enables anoperation of an on-board camera 830 to record still images, videostream, and the like.

A mobile computing device 800 implementing the system 802 may haveadditional features or functionality. For example, the mobile computingdevice 800 may also include additional data storage devices (removableand/or non-removable) such as, magnetic disks, optical disks, or tape.Such additional storage is illustrated in FIG. 8B by the non-volatilestorage area 868.

Data/information generated or captured by the mobile computing device800 and stored via the system 802 may be stored locally on the mobilecomputing device 800, as described above, or the data may be stored onany number of storage media that may be accessed by the device via theradio interface layer 872 or via a wired connection between the mobilecomputing device 800 and a separate computing device associated with themobile computing device 800, for example, a server computer in adistributed computing network, such as the Internet. As should beappreciated such data/information may be accessed via the mobilecomputing device 800 via the radio interface layer 872 or via adistributed computing network. Similarly, such data/information may bereadily transferred between computing devices for storage and useaccording to well-known data/information transfer and storage means,including electronic mail and collaborative data/information sharingsystems.

FIG. 9 illustrates one aspect of the architecture of a system forprocessing data received at a computing system from a remote source,such as a personal computer 904, tablet computing device 906, or mobilecomputing device 908, as described above. Content displayed at serverdevice 902 may be stored in different communication channels or otherstorage types. For example, various documents may be stored using adirectory service 922, a web portal 924, a mailbox service 926, aninstant messaging store 928, or a social networking site 930. Contextassociation generation component 921 may be employed by a client thatcommunicates with server device 902, and/or isolated collectionadaptation component 920 may be employed by server device 902. Theserver device 902 may provide data to and from a client computing devicesuch as a personal computer 904, a tablet computing device 906 and/or amobile computing device 908 (e.g., a smart phone) through a network 915.By way of example, the computer system described above may be embodiedin a personal computer 904, a tablet computing device 906 and/or amobile computing device 908 (e.g., a smart phone). Any of theseembodiments of the computing devices may obtain content from the store916, in addition to receiving graphical data useable to be eitherpre-processed at a graphic-originating system, or post-processed at areceiving computing system.

FIG. 9 illustrates an exemplary tablet computing device 900 that mayexecute one or more aspects disclosed herein. In addition, the aspectsand functionalities described herein may operate over distributedsystems (e.g., cloud-based computing systems), where applicationfunctionality, memory, data storage and retrieval and various processingfunctions may be operated remotely from each other over a distributedcomputing network, such as the Internet or an intranet. User interfacesand information of various types may be displayed via on-board computingdevice displays or via remote display units associated with one or morecomputing devices. For example user interfaces and information ofvarious types may be displayed and interacted with on a wall surfaceonto which user interfaces and information of various types areprojected. Interaction with the multitude of computing systems withwhich embodiments of the invention may be practiced include, keystrokeentry, touch screen entry, voice or other audio entry, gesture entrywhere an associated computing device is equipped with detection (e.g.,camera) functionality for capturing and interpreting user gestures forcontrolling the functionality of the computing device, and the like.

As will be understood from the foregoing disclosure, one aspect of thetechnology relates to a system comprising: at least one processor; and amemory storing instructions that when executed by the at least oneprocessor perform a set of operations. The set of operations comprises:receiving a request for information in an isolated collection;determining a context associated with the request for information;accessing a ruleset comprising one or more rules associated with theisolated collection; generating, based on the context and a contextassociation associated with the isolated collection, an adapted rulesetfor the ruleset; generating, using the adapted ruleset, a response tothe request for information; and providing the response in response tothe request for information. In an example, generating the adaptedruleset comprises: determining, based on the context and the contextassociation, whether each rule of the one or more rules should beincluded in the adapted ruleset; and when it is determined that a ruleof the one or more rules should be included in the adapted ruleset,selecting the rule for inclusion in the adapted ruleset. In anotherexample, generating the adapted ruleset further comprises generating,based on the context and the context association, a new rule for theadapted ruleset. In a further example, determining the context comprisesreceiving context information as part of the request for information. Inyet another example, determining the context comprises generatingcontext information based on the request for information. In a furtherstill example, the context association was generated in response to auser indication associating a context parameter with a rule of theisolated collection. In an example, the context association wasgenerated automatically based on a determination that a rule of theisolated collection is associated with a context parameter.

In another aspect, the technology relates to a computer-implementedmethod for adapting an isolated collection using a context association.The method comprises: determining a context associated with targetinformation in the isolated collection; accessing a ruleset comprisingone or more rules associated with the isolated collection; generating,based on the context and a context association associated with thetarget information, an adapted ruleset for the ruleset; generating,using the adapted ruleset, an adapted isolated collection relating tothe target information; and providing the adapted isolated collection toan application associated with the target information. In an example,generating the adapted ruleset comprises: determining, based on thecontext and the context association, whether each rule of the one ormore rules should be included in the adapted ruleset; and when it isdetermined that a rule of the one or more rules should be included inthe adapted ruleset, selecting the rule for inclusion in the adaptedruleset. In another example, generating the adapted ruleset furthercomprises generating, based on the context and the context association,a new rule for the adapted ruleset. In a further example, determiningthe context comprises receiving context information from theapplication. In yet another example, the context association wasgenerated in response to a user indication associating a contextparameter with a rule of the isolated collection. In a further stillexample, the context association was generated automatically based on adetermination that a rule of the isolated collection is associated witha context parameter.

In another aspect, the technology relates to anothercomputer-implemented method for adapting an isolated collection using acontext association associated with the isolated collection. The methodcomprises: receiving a request for information in the isolatedcollection; determining a context associated with the request forinformation; accessing a ruleset comprising one or more rules associatedwith the isolated collection; generating, based on the context and thecontext association associated with the isolated collection, an adaptedruleset for the ruleset; generating, using the adapted ruleset, aresponse to the request for information; and providing the response inresponse to the request for information. In an example generating theadapted ruleset comprises: determining, based on the context and thecontext association, whether each rule of the one or more rules shouldbe included in the adapted ruleset; and when it is determined that arule of the one or more rules should be included in the adapted ruleset,selecting the rule for inclusion in the adapted ruleset. In anotherexample, generating the adapted ruleset further comprises generating,based on the context and the context association, a new rule for theadapted ruleset. In a further example, determining the context comprisesreceiving context information as part of the request for information. Inyet another example, determining the context comprises generatingcontext information based on the request for information. In a furtherstill example, the context association was generated in response to auser indication associating a context parameter with a rule of theisolated collection. In an example, the context association wasgenerated automatically based on a determination that a rule of theisolated collection is associated with a context parameter.

Aspects of the present disclosure, for example, are described above withreference to block diagrams and/or operational illustrations of methods,systems, and computer program products according to aspects of thedisclosure. The functions/acts noted in the blocks may occur out of theorder as shown in any flowchart. For example, two blocks shown insuccession may in fact be executed substantially concurrently or theblocks may sometimes be executed in the reverse order, depending uponthe functionality/acts involved.

The description and illustration of one or more aspects provided in thisapplication are not intended to limit or restrict the scope of thedisclosure as claimed in any way. The aspects, examples, and detailsprovided in this application are considered sufficient to conveypossession and enable others to make and use the best mode of claimeddisclosure. The claimed disclosure should not be construed as beinglimited to any aspect, example, or detail provided in this application.Regardless of whether shown and described in combination or separately,the various features (both structural and methodological) are intendedto be selectively included or omitted to produce an embodiment with aparticular set of features. Having been provided with the descriptionand illustration of the present application, one skilled in the art mayenvision variations, modifications, and alternate aspects falling withinthe spirit of the broader aspects of the general inventive conceptembodied in this application that do not depart from the broader scopeof the claimed disclosure.

What is claimed is:
 1. A system comprising: at least one processor; anda memory storing instructions that when executed by the at least oneprocessor perform a set of operations comprising: receiving a requestfor information in an isolated collection, wherein the isolatedcollection comprises a first set of relationships between differentresource types for a set of resources; determining a context associatedwith the request for information; accessing a ruleset comprising one ormore rules associated with the isolated collection; generating, based onthe context and a context association associated with the isolatedcollection, an adapted ruleset for the ruleset, wherein the contextassociation is associated with a subpart of the ruleset for the isolatedcollection and the context association is based on a context parameterspecific to a characteristic of a requestor that provided the requestfor information; generating a response to the request for information inthe isolated collection, the response comprising a second set ofrelationships between the resources for the set of resources that isdifferent than the first set of relationships, wherein the second set ofrelationships is generated at least in part using the adapted ruleset;and providing the response in response to the request for information.2. The system of claim 1, wherein generating the adapted rulesetcomprises: determining, based on the context and the contextassociation, whether each rule of the one or more rules should beincluded in the adapted ruleset; and when it is determined that a ruleof the one or more rules should be included in the adapted ruleset,selecting the rule for inclusion in the adapted ruleset.
 3. The systemof claim 2, wherein generating the adapted ruleset further comprisesgenerating, based on the context and the context association, a new rulefor the adapted ruleset.
 4. The system of claim 1, wherein determiningthe context comprises receiving context information as part of therequest for information, the context information being specific to therequestor.
 5. The system of claim 1, wherein the first set ofrelationships comprises at least one asserted relationship, and whereinthe second set of relationships comprises at least one inferredrelationship generated using the adapted ruleset.
 6. The system of claim1, wherein the set of operations includes: generating the contextassociation in response to a user indication associating a contextparameter with a rule of the isolated collection; and storing thecontext association using the isolated collection.
 7. The system ofclaim 1, wherein the set of operations includes: generating the contextassociation automatically based on a determination that a rule of theisolated collection is associated with the context parameter that isspecific to the characteristic of the requestor that provided therequest for information; and storing the context association using theisolated collection.
 8. A computer-implemented method for adapting anisolated collection using a context association, the method comprising:determining a context associated with target information in the isolatedcollection, wherein the isolated collection comprises a first set ofrelationships between different resource types for a set of resources;accessing a ruleset comprising one or more rules associated with theisolated collection; generating, based on the context and a contextassociation associated with the target information, an adapted rulesetfor the ruleset, wherein the context association is associated with asubpart of the ruleset for the isolated collection and the contextassociation is based on a context parameter specific to a characteristicof a requestor that provided a request for information; generating anadapted isolated collection relating to the target information in theisolated collection, wherein the adapted isolated collection comprises asecond set of relationships between the resources for the set ofresources that is different from the first set of relationships, and thesecond set of relationships is generated at least in part using theadapted ruleset; and providing the adapted isolated collection to anapplication associated with the target information.
 9. Thecomputer-implemented method of claim 8, wherein generating the adaptedruleset comprises: determining, based on the context and the contextassociation, whether each rule of the one or more rules should beincluded in the adapted ruleset; and when it is determined that a ruleof the one or more rules should be included in the adapted ruleset,selecting the rule for inclusion in the adapted ruleset.
 10. Thecomputer-implemented method of claim 9, wherein generating the adaptedruleset further comprises generating, based on the context and thecontext association, a new rule for the adapted ruleset.
 11. Thecomputer-implemented method of claim 8, wherein determining the contextcomprises receiving context information from the application.
 12. Thecomputer-implemented method of claim 8, further comprising: generatingthe context association in response to a user indication associating acontext parameter with a rule of the isolated collection; and storingthe context association using the isolated collection.
 13. Thecomputer-implemented method of claim 8, further comprising: generatingthe context association automatically based on a determination that arule of the isolated collection is associated with the context parameterthat is specific to the characteristic of the requestor that providedthe request for information; and storing the context association usingthe isolated collection.
 14. A computer-implemented method for adaptingan isolated collection using a context association associated with theisolated collection, the method comprising: receiving a request forinformation in the isolated collection, wherein the isolated collectioncomprises a first set of relationships between different resource typesfor a set of resources; determining a context associated with therequest for information; accessing a ruleset comprising one or morerules associated with the isolated collection; generating, based on thecontext and the context association associated with the isolatedcollection, an adapted ruleset for the ruleset, wherein the contextassociation is associated with a subpart of the ruleset for the isolatedcollection and the context association is based on a context parameterspecific to a characteristic of a requestor that provided the requestfor information; generating a response to the request for informationcomprising a second set of relationships between the resources for theset of resources that is different than the first set of relationships,wherein the second set of relationships is generated at least in partbased on the adapted ruleset; and providing the response in response tothe request for information.
 15. The computer-implemented method ofclaim 14, wherein generating the adapted ruleset comprises: determining,based on the context and the context association, whether each rule ofthe one or more rules should be included in the adapted ruleset; andwhen it is determined that a rule of the one or more rules should beincluded in the adapted ruleset, selecting the rule for inclusion in theadapted ruleset.
 16. The computer-implemented method of claim 15,wherein generating the adapted ruleset further comprises generating,based on the context and the context association, a new rule for theadapted ruleset.
 17. The computer-implemented method of claim 14,wherein determining the context comprises receiving context informationas part of the request for information, the context information beingspecific to the requestor.
 18. The computer-implemented method of claim14, wherein determining the context comprises generating contextinformation based on the request for information.
 19. Thecomputer-implemented method of claim 14, further comprising: generatingthe context association in response to a user indication associating acontext parameter with a rule of the isolated collection; and storingthe context association such that it is specific to the user to which itrelates.
 20. The computer-implemented method of claim 14, furthercomprising: generating the context association automatically based on adetermination that a rule of the isolated collection is associated withthe context parameter that is specific to the characteristic of therequestor that provided the request for information; and storing thecontext association using the isolated collection.